Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle
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Somekh-2012-Conceptual Model-Bas.pdf
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2.41 MB
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Author(s)
Somekh, Judith
Choder, Mordechai
Dori, Dov
Date Issued
December 2012
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Somekh, Judith, Mordechai Choder, and Dov Dori. “Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle.” Ed. Thomas Preiss. PLoS ONE 7.12 (2012).
Version
Final published version
Abstract
We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model.
MIT Department
Massachusetts Institute of Technology. Engineering Systems Division
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0051430
